Company Intro

Based in the U.S., the company provides multi-model freight transportation and last-mile delivery, handling over a million shipments each year. It supports major industries like eCommerce, retail, and manufacturing.

To manage growing demand, they implemented a flow-based rule driven assistant along with a support team handling multichannel support across email, chat, WhatsApp, and web. The assistant worked for simple questions based on pre-defined scripts but struggled with more complex or unclear messages, making it hard to keep up with today’s fast-moving logistics needs.

Core Challenges

Even after rolling out basic automation, the company struggled with five costly support bottlenecks :

High Support Team Costs (~$2M/year):

A 24-agent team working in shifts led to high labor expenses without improved efficiency.

Poor Intent Understanding :

The existing assistant struggled to understand variations in customer intent for same repetitive queries, leading to repeated escalations for large number queries it should’ve handled.

Inefficient Routing & Escalations

Every escalation still needed a human handoff — burning time, driving up costs, and frustrating customers.

Scalability Challenges

During peak seasons, the system couldn’t scale to meet surge demands without overloading the support team.

Limited Visibility & Analytics

With no real-time analytics, the team had limited understanding of customer sentiment, recurring issues, or agent performance, making CX improvements difficult.

The Cost of Inaction

The Hidden Cost of Staying Manual

$800K+ wasted yearly on redundant support labour
100K+ queries that could have been resolved automatically
Rising Customer churn due to slow, inaccurate responses
No actionable data or insights to improve CX

Objectives

The company sought to reimagine its support infrastructure by integrating AI-powered automation to :

Automate repetitive and intent-based customer queries.
Reduce support costs while enhancing CX.
Improve CX through faster & accurate responses
Enabling smart, intent-based ticket routing.
Ensure scalability during high-demand periods
Centralize support data with KPI-driven decision-making.

Evolution Process: From Flow Bots to Full AI Intelligence

The company first adopted flow-based rule-driven assistants several years ago as to automate shipment tracking and confirming order status. Initially, this reduced ticket volume and brought small wins. However, with customer expectations evolved and inquiries became more nuanced, these assistants proved rigid and outdated.

Customers often phrased questions differently than the flow allowed for, leading to frequent “I didn’t understand” replies.
Complex issues still required agent involvement, clogging queues.
Escalations surged 12% YoY — a clear red flag that flowbots were falling short.

To improve CX & operational efficiency, the leadership connected with us to explore a strategic AI upgrade. After several internal workshops, competitor benchmarking, and pilot discussions, a complete transition was envisioned for next-gen AI assistant and smart AI agent routing system.

Implementation Process (Phased Rollout)

The implementation was executed in five structured phases over a 6-month window.

Phase 1. Platform Selection & Architecture Design :

Chose OpenAI GPT-4, Dialogflow, and proprietary AI agent routing as the core tech stack.
Built on secure private cloud with GDPR and SOC 2 compliance.

Phase 2. Problem Discovery & Strategic planning :

Trained AI on 12 months of historical support data (e.g., tracking, rescheduling, disputes).
Conducted deep-dive workshops with operations and support teams to map failure patterns and built use-case-specific objectives
Created use-case-specific goals, hybrid escalation paths, and trained custom NLP models for logistics terms.

Phase 3. System Integration :

Integrated seamlessly with existing platforms :

Legacy CRM : To pull customer data and ticket history
Shipment Tracking System (API-based) : For real-time updates
ERP (SAP): To manage scheduling, dispatch, POD documents, and exceptions
Helpdesk : For sorting tickets based on complexity and intent

Our AI agents actively pulled data from these integrations and automate number of tasks such as :

Automate routine updates like change in address, Log tickets with full context.
Pre-fill forms, escalate high-priority tickets, and respond with verified data
Assist live agents with real-time data lookups and reply suggestions
Generate daily/weekly summaries of fulfilment KPIs, shipment SLAs, etc.
Auto-generate BOLs, invoices, packing slips, and shipping labels

Phase 4. Fine-Tuning & Real-Time Learning :

Continuous learning was initiated using anonymized support transcripts
Real-Time Fine-Tuning Challenge: The assistant initially confused "warehouse delivery delays" with "in-transit shipment delays" due to overlapping training data. Our team identified the issue via performance logs and fine-tuned the model using RLHF (Reinforcement Learning from Human Feedback).
Misclassification of “change pickup” as “reschedule delivery” was resolved with clarifying prompts and NLP refinement.

Phase 5. Rollout & Training :

Initial deployment started with internal agent co-piloting, where AI suggestions assisted agents in real time.
After 6 months of testing and feedback, the AI assistant was launched across web, app, and email.
Staff training sessions were conducted to ensure adoption, with dashboards introduced for agent visibility and override control.

Capabilities

The newly implemented AI assistant and AI agents transformed the support process with capabilities tailor-made for the logistics industry :

AI Assistant Highlights :

Advanced Intent Recognition

Understands varied phrasing and context for more natural conversations.

24/7 Autonomous Support

Resolves 40–60% of daily queries like tracking, rescheduling, and pricing without human help.

Dynamic Query Routing

Directs queries based on urgency, intent, and customer type for faster resolution.

Sentiment & VIP Detection

Flags dissatisfied customers and prioritizes high-value clients for white-glove service.

Insight-Driven Actions

Collects feedback, monitors KPIs, and tracks CSAT to improve service quality.

Other

+ Other support tasks like real-time tracking, agent onboarding, and survey handling managed seamlessly.

AI Agent Highlights :

System Integration &
Data Retrieval :

Pulls real-time data from CRM, ERP, and Helpdesk to enrich responses.

Smart Escalation & Response Generation :

Suggests replies, pre-fills forms, and routes complex queries with full context.

Other :

+ Supports human agents through collaboration, operational automation, reducing errors and boosting efficiency.

Tech Stack

Frontend

React.js, Flutter

Backend

FastAPI, Dialogflow

Database

PostgreSQL, Redis

AI/ML

OpenAI GPT, Dialogflow, RLHF filters

Routing & Orchestration

Dialogflow Webhooks, Proprietary AI Router

Integration

REST APIs, Webhooks, Freshdesk SDK, WhatsApp API

Cloud

AWS (EC2, S3, Lambda, RDS)

Messaging

Twilio, Firebase Cloud Messaging, WebSockets

Monitoring & Analytics

Prometheus, Grafana, Dialogflow Analytics

Results & Business Impact

Through the implementation of AI assistants and smart AI agents, the logistics company experienced a dramatic operational and financial uplift.

Top Strategic Outcomes

$812K+ in Annual Support Savings, lowering total cost by over 40% with enhanced support quality.

58.4% Reduction in Average Handling Time, from 15–20 minutes to under 6 minutes per query.

52% Query Deflection, with over 500 daily queries now resolved autonomously.

Operational Efficiency

Metric	Before AI System	After AI Assistant + Agents	Change (%)
Daily Query Volume	~800–1,000	950 avg., 500+ auto-resolved	↑ 18% throughput
Average Handling Time	15–20 min	< 6 min	↓ 58%
First-Contact Resolution	62%	88%	↑ 26%
Routing Accuracy	65–70% manual	>92% AI-routed	↑ 30%
CSAT	72%	89%	↑ 17%
Query Understanding	Tree-based, low context	NLP-driven, multi-turn clarification	↑ Context Accuracy
Sentiment Awareness	None	Live sentiment & feedback detection	Proactive Handling

Qualitative Wins

Leadership Insights :

Centralized dashboard with KPIs, sentiment tracking, and issue trends.

Faster Escalation :

Context-aware escalations reduced agent dependency and resolution cycles.

New Agent Enablement :

Onboarding time halved with AI-curated historical insights and live reply suggestions.

Leadership Insight

We were overwhelmed by repetitive queries and rising support costs. AI helped us turn that around—automating responses, easing agent load, and delivering faster, smarter service.

Director of Operations

Future Outlook

Company plans to build on this success with several forward-looking initiatives :

Integration of voice bots for phone-based support powered by the same NLP engine.

Proactive customer outreach - notifying customers about potential delays, alternate delivery slots, & personalized alerts.

Using AI insights to refine CX strategy, optimize delivery workflows, and support demand forecasting.

Testimonials

Our Slam Book

Tony Lehtimaki

DIRECTOR - AMEOS

Spain

Very professional, accurate and efficient team despite all the changes I had them do. I look forward to working with them again.

Antoine de Bausset

CEO - BEESPOKE

France

They are great at what they do. Very easy to communicate with and they came through faster than I hoped. They delivered everything I wanted and more! I will certainly use them again!

Vivek Singh

MARKETING & SALES HEAD - VARMORA

Gujarat

I really liked their attention to detail and their sheer will to do the job at hand as good as possible beyond professional boundaries.

Nimesh Patel

DIRECTOR - COVERTEK CERAMICA

Gujarat

Excellent work, and on time with all goals. Communication was very easy, and knowledge of work was excellent. Will be working with them on upcoming projects. I highly recommend.

Craig Zappa

DIRECTOR - ENA PARAMUS

United States

"I would like to recommend their name to one and all. No doubt" their web app development services cater to all needs.

Neil Lockwood

CO-FOUNDER - ESR

Australia

Aglowid is doing a great job in the field of web app development. I am truly satisfied with their quality of service.

Daphne Christoforidou

CEO - ELEMENTIA